def _linesegproj(self, qpt, p1, p2):
"""Projects the query point onto the line segment spanned by p1 and p2.
Returns (projected pt, percentage along line p1 -> p2 (which are at 0 and 1), min dist)."""
from nkpylib.nkutils import getTriAltitude
# get the projection
proj = getTriAltitude(qpt, p1, p2)
d = -1
for i in range(len(p1)):
if p1[i] == p2[i]: continue # find a dimension with some change
loc = lerp(proj[i], (p1[i], 0.0), (p2[i], 1.0))
if loc < 0: # off the segment, closer to p1
d = self.distfunc(qpt, p1)
break
if loc > 1.0: # off the segment, closer to p2
d = self.distfunc(qpt, p2)
break
# valid projection, so d = its length
d = self.distfunc(qpt, proj)
break
# at this point, if we didn't find any non-zero dimensions,
# then we can pick either endpoint as our target. We set location to be None
if d < 0:
d = self.distfunc(qpt, p1)
loc = None
return (proj, loc, d)
def interpolate(self, qi):
"""Finds the linear segment where this query index falls and interpolates values"""
idxs = self.indexes
i, I = self._nearestindexlocs(qi)
if i == I: return self.pts[i] # one of the endpoints
# index
x, X = idxs[i], idxs[I]
# lerp each dim of the output
ret = self.copypt(self.pts[0])
for dim, (y, Y) in enumerate(zip(self.pts[i], self.pts[I])):
ret[dim] = lerp(qi, (x,y), (X,Y))
return ret
def project(self, qpt):
"""Projects a query point onto the closest line segment to find its equivalent index and pt.
Returns (projected index, projected point, projection distance)"""
mind = self.distfunc(qpt, self.pts[0])
ret = (self.indexes[0], self.pts[0], mind)
for p1, p2, i1, i2 in zip(self.pts, self.pts[1:], self.indexes, self.indexes[1:]):
proj, loc, d = self._linesegproj(qpt, p1, p2)
if d > mind: continue
# possible candidate for best
mind = d
# check loc to see whether the projected point is one of the endpoints
if loc < 0:
# the first point
ret = (i1, p1, d)
elif loc > 1:
# the 2nd point
ret = (i2, p2, d)
else:
# somewhere in between
ret = (lerp(loc, (0.0, i1), (1.0, i2)), proj, d)
return ret
